anshy047/fake-news-detector-transformer

🧠 Fake News Detection using Transformer

This model is a fine-tuned DistilBERT model designed to classify news articles as FAKE or REAL.

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🚀 Model Overview

• Base Model: distilbert-base-uncased
• Task: Text Classification
• Labels: FAKE, REAL
• Architecture: Transformer-based (DistilBERT)

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📊 Performance

• Accuracy: ~98%
• F1 Score: ~0.98

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📂 Dataset

Trained on a combined dataset including:

• Fake news datasets
• Real news datasets
• Cleaned and preprocessed text corpus

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🧠 How It Works

The model analyzes:

• Semantic meaning of text
• Contextual relationships
• Writing patterns

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⚡ Usage

from transformers import pipeline

classifier = pipeline("text-classification", model="your-username/your-model")

classifier("Breaking news: Scientists discover new planet")